Mining non-redundant association rules

Mohammed J. Zaki

Research output: Contribution to journalArticle

278 Citations (Scopus)

Abstract

The traditional association rule mining framework produces many redundant rules. The extent of redundancy is a lot larger than previously suspected. We present a new framework for associations based on the concept of closed frequent itemsets. The number of non-redundant rules produced by the new approach is exponentially (in the length of the longest frequent itemset) smaller than the rule set from the traditional approach. Experiments using several "hard" as well as "easy" real and synthetic databases confirm the utility of our framework in terms of reduction in the number of rules presented to the user, and in terms of time.

Original languageEnglish
Pages (from-to)223-248
Number of pages26
JournalData Mining and Knowledge Discovery
Volume9
Issue number3
DOIs
Publication statusPublished - 1 Nov 2004

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Keywords

  • Association rule mining
  • Formal concept analysis
  • Frequent closed itemsets

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computer Networks and Communications

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